Data mining has been defined as

The nontrivial extraction of implicit, previously unknown, and potentially useful information from data

and

The science of extracting useful information from large data sets or databases.

Well, in simpler terms, data-mining is what you do when you are unable to know your customers as you would if you were living and working in a small community. It might be so just because you have more customers than you can know as an individual, but you are still ignoring your customers’ wants and needs. And they don’t like it. Thats where data mining comes in.

Data Mining studies how to analyze the flood of information generated by businesses, science, web, and other sources. It uses methods from several fields, including databases, machine learning, statistics, and information visualization and it focuses on key tasks such as classification, clustering, market basket analysis or association rules, and link analysis.

Although it is usually used in relation to analysis of data, data mining, like artificial intelligence, is an umbrella term and is used with varied meaning in a wide range of contexts.

As Michael Meltzer points out in this DM Direct Special Report article, you need to get closer to your actual and potential customers given the large number of relationships an organization must manage, and [with] the readily available technology you can!.

Look at Amazon.com. They deliver to us the best user experience by customizing it for each individual customer, and thats why we keep going back to it.